Real-time image detection for edge devices: a peach fruit detection application
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.11/8159 |
Resumo: | Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applications, such as robot vision in orchards, require computer vision models to run on edge devices while performing inferences at high speed. In this area, most modern applications use an integrated graphics processing unit (GPU). In this work, we propose the use of a tensor processing unit (TPU) accelerator with a Raspberry Pi target device and the state-of-the-art, lightweight, and hardware-aware MobileDet detector model. Our contribution is the extension of the possibilities of using accelerators (the TPU) for edge devices in precision agriculture. The proposed method was evaluated using a novel dataset of peaches with three cultivars, which will be made available for further studies. The model achieved an average precision (AP) of 88.2% and a performance of 19.84 frames per second (FPS) at an image size of 640 × 480. The results obtained show that the TPU accelerator can be an excellent alternative for processing on the edge in precision agriculture. |
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Real-time image detection for edge devices: a peach fruit detection applicationDeep learningEdge deviceObject detectionPrecision agricultureTPU acceleratorWithin the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applications, such as robot vision in orchards, require computer vision models to run on edge devices while performing inferences at high speed. In this area, most modern applications use an integrated graphics processing unit (GPU). In this work, we propose the use of a tensor processing unit (TPU) accelerator with a Raspberry Pi target device and the state-of-the-art, lightweight, and hardware-aware MobileDet detector model. Our contribution is the extension of the possibilities of using accelerators (the TPU) for edge devices in precision agriculture. The proposed method was evaluated using a novel dataset of peaches with three cultivars, which will be made available for further studies. The model achieved an average precision (AP) of 88.2% and a performance of 19.84 frames per second (FPS) at an image size of 640 × 480. The results obtained show that the TPU accelerator can be an excellent alternative for processing on the edge in precision agriculture.Repositório Científico do Instituto Politécnico de Castelo BrancoAssunção, EduardoGaspar, Pedro D.Alibabaei, KhadijehSimões, M.P.Proença, HugoSoares, Vasco N.G.J.Caldeira, J.M.L.P.2022-11-09T09:20:44Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.11/8159engASSUNÇÃO, Eduardo [et al.] (2022) - Real-time image detection for edge devices: a peach fruit detection application. Future Internet. 14:11. DOI: https://doi.org/10.3390/fi14110323.10.3390/fi14110323info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-10T01:48:38Zoai:repositorio.ipcb.pt:10400.11/8159Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:38:34.821314Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Real-time image detection for edge devices: a peach fruit detection application |
title |
Real-time image detection for edge devices: a peach fruit detection application |
spellingShingle |
Real-time image detection for edge devices: a peach fruit detection application Assunção, Eduardo Deep learning Edge device Object detection Precision agriculture TPU accelerator |
title_short |
Real-time image detection for edge devices: a peach fruit detection application |
title_full |
Real-time image detection for edge devices: a peach fruit detection application |
title_fullStr |
Real-time image detection for edge devices: a peach fruit detection application |
title_full_unstemmed |
Real-time image detection for edge devices: a peach fruit detection application |
title_sort |
Real-time image detection for edge devices: a peach fruit detection application |
author |
Assunção, Eduardo |
author_facet |
Assunção, Eduardo Gaspar, Pedro D. Alibabaei, Khadijeh Simões, M.P. Proença, Hugo Soares, Vasco N.G.J. Caldeira, J.M.L.P. |
author_role |
author |
author2 |
Gaspar, Pedro D. Alibabaei, Khadijeh Simões, M.P. Proença, Hugo Soares, Vasco N.G.J. Caldeira, J.M.L.P. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico de Castelo Branco |
dc.contributor.author.fl_str_mv |
Assunção, Eduardo Gaspar, Pedro D. Alibabaei, Khadijeh Simões, M.P. Proença, Hugo Soares, Vasco N.G.J. Caldeira, J.M.L.P. |
dc.subject.por.fl_str_mv |
Deep learning Edge device Object detection Precision agriculture TPU accelerator |
topic |
Deep learning Edge device Object detection Precision agriculture TPU accelerator |
description |
Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applications, such as robot vision in orchards, require computer vision models to run on edge devices while performing inferences at high speed. In this area, most modern applications use an integrated graphics processing unit (GPU). In this work, we propose the use of a tensor processing unit (TPU) accelerator with a Raspberry Pi target device and the state-of-the-art, lightweight, and hardware-aware MobileDet detector model. Our contribution is the extension of the possibilities of using accelerators (the TPU) for edge devices in precision agriculture. The proposed method was evaluated using a novel dataset of peaches with three cultivars, which will be made available for further studies. The model achieved an average precision (AP) of 88.2% and a performance of 19.84 frames per second (FPS) at an image size of 640 × 480. The results obtained show that the TPU accelerator can be an excellent alternative for processing on the edge in precision agriculture. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-09T09:20:44Z 2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.11/8159 |
url |
http://hdl.handle.net/10400.11/8159 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
ASSUNÇÃO, Eduardo [et al.] (2022) - Real-time image detection for edge devices: a peach fruit detection application. Future Internet. 14:11. DOI: https://doi.org/10.3390/fi14110323. 10.3390/fi14110323 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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